Book description
This new text offers uptodate coverage on the principles of digital communications, focusing on core principles and relating theory to practice.
Numerous examples, worked out in detail, have been included to help the student develop an intuitive grasp of the theory. The text also incorporates MATLABbased computer experiments throughout, as well as themed examples and an abundance of homework problems.
Table of contents
 Coverpage
 Titlepage
 Copyright
 Dedication
 Preface
 Contents
 1 Introduction

2 Fourier Analysis of Signals and Systems
 2.1 Introduction
 2.2 The Fourier Series
 2.3 The Fourier Transform
 2.4 The Inverse Relationship between TimeDomain and FrequencyDomain Representations
 2.5 The Dirac Delta Function
 2.6 Fourier Transforms of Periodic Signals
 2.7 Transmission of Signals through Linear TimeInvariant Systems
 2.8 Hilbert Transform
 2.9 Preenvelope
 2.10 Complex Envelopes of BandPass Signals
 2.11 Canonical Representation of BandPass Signals
 2.12 Complex LowPass Representations of BandPass Systems
 2.13 Putting the Complex Representations of BandPass Signals and Systems All Together
 2.14 Linear Modulation Theory
 2.15 Phase and Group Delays
 2.16 Numerical Computation of the Fourier Transform
 2.17 Summary and Discussion

3 Probability Theory and Bayesian Inference
 3.1 Introduction
 3.2 Set Theory
 3.3 Probability Theory
 3.4 Random Variables
 3.5 Distribution Functions
 3.6 The Concept of Expectation
 3.7 SecondOrder Statistical Averages
 3.8 Characteristic Function
 3.9 The Gaussian Distribution
 3.10 The Central Limit Theorem
 3.11 Bayesian Inference
 3.12 Parameter Estimation
 3.13 Hypothesis Testing
 3.14 Composite Hypothesis Testing
 3.15 Summary and Discussion

4 Stochastic Processes
 4.1 Introduction
 4.2 Mathematical Definition of a Stochastic Process
 4.3 Two Classes of Stochastic Processes: Strictly Stationary and Weakly Stationary
 4.4 Mean, Correlation, and Covariance Functions of Weakly Stationary Processes
 4.5 Ergodic Processes
 4.6 Transmission of a Weakly Stationary Process through a Linear Timeinvariant Filter
 4.7 Power Spectral Density of a Weakly Stationary Process
 4.8 Another Definition of the Power Spectral Density
 4.9 Crossspectral Densities
 4.10 The Poisson Process
 4.11 The Gaussian Process
 4.12 Noise
 4.13 Narrowband Noise
 4.14 Sine Wave Plus Narrowband Noise
 4.15 Summary and Discussion

5 Information Theory
 5.1 Introduction
 5.2 Entropy
 5.3 Sourcecoding Theorem
 5.4 Lossless Data Compression Algorithms
 5.5 Discrete Memoryless Channels
 5.6 Mutual Information
 5.7 Channel Capacity
 5.8 Channelcoding Theorem
 5.9 Differential Entropy and Mutual Information for Continuous Random Ensembles
 5.10 Information Capacity Law
 5.11 Implications of the Information Capacity Law
 5.12 Information Capacity of Colored Noisy Channel
 5.13 Rate Distortion Theory
 5.14 Summary and Discussion

6 Conversion of Analog Waveforms into Coded Pulses
 6.1 Introduction
 6.2 Sampling Theory
 6.3 PulseAmplitude Modulation
 6.4 Quantization and its Statistical Characterization
 6.5 PulseCode Modulation
 6.6 Noise Considerations in PCM Systems
 6.7 PredictionError Filtering for Redundancy Reduction
 6.8 Differential PulseCode Modulation
 6.9 Delta Modulation
 6.10 Line Codes
 6.11 Summary and Discussion

7 Signaling over AWGN Channels
 7.1 Introduction
 7.2 Geometric Representation of Signals
 7.3 Conversion of the Continuous AWGN Channel into a Vector Channel
 7.4 Optimum Receivers Using Coherent Detection
 7.5 Probability of Error
 7.6 PhaseShift Keying Techniques Using Coherent Detection
 7.7 Mary Quadrature Amplitude Modulation
 7.8 FrequencyShift Keying Techniques Using Coherent Detection
 7.9 Comparison of Mary PSK and Mary FSK from an InformationTheoretic Viewpoint
 7.10 Detection of Signals with Unknown Phase
 7.11 Noncoherent Orthogonal Modulation Techniques
 7.12 Binary FrequencyShift Keying Using Noncoherent Detection
 7.13 Differential PhaseShift Keying
 7.14 BER Comparison of Signaling Schemes over AWGN Channels
 7.15 Synchronization
 7.16 Recursive Maximum Likelihood Estimation for Synchronization
 7.17 Summary and Discussion

8 Signaling over BandLimited Channels
 8.1 Introduction
 8.2 Error Rate Due to Channel Noise in a MatchedFilter Receiver
 8.3 Intersymbol Interference
 8.4 Signal Design for Zero ISI
 8.5 Ideal Nyquist Pulse for Distortionless Baseband Data Transmission
 8.6 RaisedCosine Spectrum
 8.7 SquareRoot RaisedCosine Spectrum
 8.8 PostProcessing Techniques: The Eye Pattern
 8.9 Adaptive Equalization
 8.10 Broadband Backbone Data Network: Signaling over Multiple Baseband Channels
 8.11 Digital Subscriber Lines
 8.12 Capacity of AWGN Channel Revisited
 8.13 Partitioning ContinuousTime Channel into a Set of Subchannels
 8.14 WaterFilling Interpretation of the Constrained Optimization Problem
 8.15 DMT System Using Discrete Fourier Transform
 8.16 Summary and Discussion

9 Signaling over Fading Channels
 9.1 Introduction
 9.2 Propagation Effects
 9.3 Jakes Model
 9.4 Statistical Characterization of Wideband Wireless Channels
 9.5 FIR Modeling of Doubly Spread Channels
 9.6 Comparison of Modulation Schemes: Effects of Flat Fading
 9.7 Diversity Techniques
 9.8 “Space DiversityonReceive” Systems
 9.9 “Space DiversityonTransmit” Systems
 9.10 “MultipleInput, MultipleOutput” Systems: Basic Considerations
 9.11 MIMO Capacity for Channel Known at the Receiver
 9.12 Orthogonal Frequency Division Multiplexing
 9.13 Spread Spectrum Signals
 9.14 CodeDivision Multiple Access
 9.15 The RAKE Receiver and Multipath Diversity
 9.16 Summary and Discussion

10 ErrorControl Coding
 10.1 Introduction
 10.2 Error Control Using Forward Error Correction
 10.3 Discrete Memoryless Channels
 10.4 Linear Block Codes
 10.5 Cyclic Codes
 10.6 Convolutional Codes
 10.7 Optimum Decoding of Convolutional Codes
 10.8 Maximum Likelihood Decoding of Convolutional Codes
 10.9 Maximum a Posteriori Probability Decoding of Convolutional Codes
 10.10 Illustrative Procedure for Map Decoding in the LogDomain
 10.11 New Generation of Probabilistic Compound Codes
 10.12 Turbo Codes
 10.13 EXIT Charts
 10.14 LowDensity ParityCheck Codes
 10.15 TrellisCoded Modulation
 10.16 Turbo Decoding of Serial Concatenated Codes
 10.17 Summary and Discussion
 A Advanced Probabilistic Models
 B Bounds on the QFunction
 C Bessel Functions
 D Method of Lagrange Multipliers
 E Information Capacity of MIMO Channels
 F Interleaving
 G The PeakPower Reduction Problem in OFDM
 H Nonlinear SolidState Power Amplifiers
 I Monte Carlo Integration
 J MaximalLength Sequences
 K Mathematical Tables
 Glossary
 Bibliography
 Index
 Credits
Product information
 Title: Digital Communication Systems
 Author(s):
 Release date: February 2013
 Publisher(s): Wiley
 ISBN: 9780471647355
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